Respiration monitoring for heart failure using implantable device

ABSTRACT

An implantable respiration monitor can be used to detect disordered breathing or periodic breathing events that can be categorized, such as according to one or more of sleep, exercise, and resting awake states. The categorized frequency of such events can be compared to independently specifiable thresholds, such as to trigger an alert or responsive therapy, or to display one or more trends. The information can also be combined with detection of one or more other congestive heart failure (CHF) symptoms to generate a CHF status indicator or to trigger an alarm or responsive therapy or to display one or more trends. The alert can notify the patient or a caregiver, such as via remote monitoring. The sleep state information can be further categorized according to central sleep apnea (CSA) or obstructive sleep apnea (OSA) events.

TECHNICAL FIELD

This patent document pertains generally to disordered breathing andcongestive heart failure and more particularly, but not by way oflimitation, to categorizing, such as by using sleep and exercise states,respiration monitored using implantable device, such as for heartfailure status monitoring.

BACKGROUND

Sleep is generally beneficial and restorative to a person. Therefore, itexerts a great influence on a person's quality of life. The humansleep/wake cycle generally conforms to a circadian rhythm that isregulated by a biological clock. Regular periods of sleep enable thebody and mind to rejuvenate and rebuild. The body may perform varioustasks during sleep, such as organizing long term memory, integrating newinformation, and renewing tissue and other body structures.

Lack of sleep and/or decreased sleep quality may have a number of causalfactors including, e.g., respiratory disturbances, nerve or muscledisorders, and emotional conditions, such as depression and anxiety.Chronic long-term sleep-related disorders such as chronic insomnia,sleep-disordered breathing, and sleep movement disorders maysignificantly affect a patient's sleep quality and quality of life.

Sleep apnea, for example, is a fairly common breathing disordercharacterized by periods of interrupted breathing experienced duringsleep. Sleep apnea is typically classified based on its etiology. Onetype of sleep apnea, denoted as obstructive sleep apnea, occurs when thepatient's airway is obstructed by the collapse of soft tissue in therear of the throat. Central sleep apnea is caused by a derangement ofthe central nervous system control of respiration. The patient ceases tobreathe when control signals from the brain to the respiratory musclesare absent or interrupted. Mixed apnea is a combination of the centraland obstructive sleep apnea types. Regardless of the type of apneapeople experiencing an apnea event stop breathing for a period of time.The cessation of breathing may occur repeatedly during sleep, sometimeshundreds of times a night and occasionally for a minute or longer.

In addition to apnea, other types of disordered breathing have beenidentified, including, for example, hypopnea (shallow breathing),dyspnea (labored breathing), hyperpnea (deep breathing), and tachypnea(rapid breathing). Combinations of the disordered respiratory eventsdescribed above have also been observed. For example, Cheyne-Stokesrespiration (CSR, which is sometimes referred to as periodic breathing)is associated with rhythmic increases and decreases in tidal volumecaused by alternating periods of hyperpnea followed by apnea orhypopnea. The breathing interruptions of CSR may be associated withcentral apnea, or may be obstructive in nature. CSR is frequentlyobserved in patients with congestive heart failure (CHF) and isassociated with an increased risk of accelerated CHF progression.

OVERVIEW

An implantable respiration monitor can be used to detect disorderedbreathing or periodic breathing events that can be categorized, such asaccording to one or more of sleep, exercise, and resting awake states.The categorized frequency of such events can be compared toindependently specifiable thresholds, such as to trigger an alert orresponsive therapy, or to display one or more trends. The informationcan also be combined with detection of one or more other congestiveheart failure (CHF) symptoms to generate a CHF status indicator or totrigger an alarm or responsive therapy or to display one or more trends.The alert can notify the patient or a caregiver, such as via remotemonitoring. The sleep state information can be further categorizedaccording to central sleep apnea (CSA) or obstructive sleep apnea (OSA)events.

In Example 1, a system includes a sleep detector, adapted to detect asleep indication in a subject, the sleep indication providing anindication or inference of whether the subject is asleep or awake. Thesystem also includes an exercise detector, adapted to detect an exerciseindication in the subject, the exercise indication providing anindication or inference of whether the subject is active or at rest. Thesystem also includes an implantable respiration monitor, operativelycoupled to the sleep and exercise detectors, the respiration monitoradapted to detect disordered breathing in the subject, and to compute atleast two of: a sleep disordered breathing indication, an exercisedisordered breathing indication, and a resting awake disorderedbreathing indication.

In Example 2, the system of Example 1 optionally includes an alertmodule, operatively coupled to the respiration monitor, the alert modulegenerating an alert in response to an abnormal value of at least one of:the sleep disordered breathing indication, the exercise disorderedbreathing indication, and the resting awake disordered breathingindication.

In Example 3, the system of Examples 1-2 optionally includes anambulatory therapy module, operatively coupled to the alert module, theambulatory therapy module configured to automatically initiate or adjusttherapy in response to the alert.

In Example 4, the system of Examples 1-3 optionally includes an alertmodule, operatively coupled to the respiration monitor, the alert modulegenerating an alert in response to at least a specified increase in atleast one of the sleep disordered breathing indication, the exercisedisordered breathing indication, and the resting awake disorderedbreathing indication.

In Example 5, the system of Examples 1-4 optionally includes anambulatory therapy module, operatively coupled to the alert module, theambulatory therapy module configured to automatically initiate or adjusttherapy in response to the alert.

In Example 6, the system of Examples 1-5 optionally includes an alertmodule, operatively coupled to the respiration monitor, the alert modulegenerating an alert in response to at least an abnormal value or aspecified increase in at least two of: the sleep disordered breathingindication, the exercise disordered breathing indication, and theresting awake disordered breathing indication.

In Example 7, the system of Examples 1-6 optionally includes anambulatory therapy module, operatively coupled to the alert module, theambulatory therapy module configured to automatically initiate or adjusttherapy in response to the alert.

In Example 8, the system of Examples 1-7 optionally include an auxiliarycongestive heart failure (CHF) indication detector, and an alert module,operatively coupled to the respiration monitor and the auxiliary CHFindication detector, the alert module generating an alert in response toan indication of CHF received from the CHF indication detector and anabnormal value or a specified increase of at least one of: the sleepdisordered breathing indication, the exercise disordered breathingindication, and the resting awake disordered breathing indication.

In Example 9, the system of Examples 1-8 are optionally configured suchthat the auxiliary CHF indication detector includes a pulmonary fluidstatus indicator, and in which the indication of CHF received from theCHF indication detector includes an indication of an abnormally highlevel of pulmonary fluid.

In Example 10, the system of Examples 1-9 are optionally configured suchthat the auxiliary CHF indication detector includes at least one of apulmonary artery pressure sensor, a heart sound sensor, a heart ratevariability detector, a patient weight indicator, and a patient activitydetector.

In Example 11, the system of Examples 1-10 optionally include anambulatory therapy module, operatively coupled to the alert module, theambulatory therapy module configured to automatically initiate or adjusttherapy in response to the alert.

In Example 12, the system of Examples 1-11 is optionally configured suchthat the respiration monitor comprises a respiration detector circuit,adapted to detect a respiration signal from the subject, an envelopedetector circuit, adapted to detect an envelope of the respirationsignal, and an envelope variation detector circuit, adapted to detect avariation in the envelope representing disordered breathing.

In Example 13, the system of Examples 1-12 is optionally configured suchthat the respiration monitor comprises means for detecting a respirationsignal from the subject, and means for detecting separate indications ofperiodic breathing in each of sleep, exercise, and resting awake states.

In Example 14, the system of Examples 1-13 optionally includes anexternal display configured to display information about at least one ofa sleep disordered breathing indication, an exercise disorderedbreathing indication, and a resting awake disordered breathingindication.

In Example 15, the system of Examples 1-14 optionally is configured suchthat it includes a display that is configured to display a trend overtime of at least one of a sleep disordered breathing indication, anexercise disordered breathing indication, and a resting awake disorderedbreathing indication.

In Example 16, the system of Examples 1-15 optionally includes an apneaclassifier, configured to distinguish between obstructive sleep apnea(OSA) and central sleep apnea (CSA), and the sleep disordered breathingindication uses information from the apnea classifier to determine thesleep disordered breathing indication.

In Example 17, a method includes monitoring respiration of a subject,detecting sleep of the subject, detecting exercise of the subject, anddetermining at least two of a sleep disordered breathing indication, anexercise disordered breathing indication and a resting awake disorderedbreathing indication.

In Example 18, the method of Example 17 optionally includes generatingan alert in response to an abnormal value of at least one of: the sleepdisordered breathing indication, the exercise disordered breathingindication, and the resting awake disordered breathing indication.

In Example 19, the method of Examples 17-18 optionally includesautomatically delivering a therapy in response to the alert.

In Example 20, the method of Examples 17-19 optionally includesmonitoring an auxiliary indication of congestive heart failure of thesubject, and generating an alert in response to an abnormal value of theauxiliary indication of congestive heart failure and an abnormal valueof at least one of: the sleep disordered breathing indication, theexercise disordered breathing indication, and the resting awakedisordered breathing indication.

In Example 21, the method of Examples 17-20 is optionally configuredsuch that the monitoring an auxiliary indication of congestive heartfailure includes monitoring at least one of a pulmonary fluidaccumulation, a pulmonary artery pressure, a heart sound, a heart ratevariability, a patient weight, and a patient activity level.

In Example 22, the method of Examples 17-21 optionally includesautomatically delivering a therapy in response to the alert.

In Example 23, the method of Examples 17-22 optionally includesdetermining a sleep disordered breathing indication, an exercisedisordered breathing indication and a resting awake disordered breathingindication.

In Example 24, the method of Examples 17-23 optionally includesgenerating an alert in response to an abnormal value or a specifiedincrease of at least two of the sleep disordered breathing indication,the exercise disordered breathing indication, and the resting awakedisordered breathing indication.

In Example 25, the method of Examples 17-24 optionally includesautomatically delivering a therapy in response to the alert.

In Example 26, the method of Examples 17-25 optionally includesdisplaying information about at least one of a sleep disorderedbreathing indication, an exercise disordered breathing indication, and aresting awake disordered breathing indication.

In Example 27, the method of Examples 17-26 optionally includesdetecting one or more apnea events, classifying the one or more apneaevents as obstructive sleep apnea (OSA) or central sleep apnea (CSA),and determining the sleep disordered breathing indication usinginformation about the classification of the one or more apnea events asOSA or CSA.

In Example 28, the method of Examples 17-27 optionally includesdetermining a first sleep disordered breathing indication using only CSAevents.

In Example 29, the method of Examples 17-27 optionally includesdetermining a second sleep disordered breathing indication using onlyOSA events.

This overview is intended to provide an overview of the subject matterof the present patent application. It is not intended to provide anexclusive or exhaustive explanation of the invention. The detaileddescription is included to provide further information about the subjectmatter of the present patent application.

BRIEF DESCRIPTION OF THE DRAWINGS

In the drawings, which are not necessarily drawn to scale, like numeralsdescribe substantially similar components throughout the several views.Like numerals having different letter suffixes represent differentinstances of substantially similar components. The drawings illustrategenerally, by way of example, but not by way of limitation, variousembodiments discussed in the present document.

FIG. 1 is a block diagram illustrating generally an example of a systemincluding an implantable device, which is typically wirelesslycommunicatively coupled by a communication module to an external localinterface, which, in turn is communicatively coupled to an externalremote server, such as over a wired or wireless telecommunications orcomputer network.

FIG. 2 is a flow chart illustrating generally an example of portions ofa technique for monitoring disordered breathing.

FIG. 3 is a flow chart illustrating generally an example of how theindicators of disordered breathing density or frequency during sleep,exercise, and rest can be used.

FIG. 4 is a flow chart illustrating generally an example of how suchindicators can be used to form a combined metric.

FIG. 5 is a flow chart, similar to FIG. 2, but illustrating a techniquein which a periodic breathing (PB) event is detected, instead of thedetecting of a disordered breathing (DB) event in FIG. 2.

FIG. 6 is a block diagram of an example, similar to FIG. 1, in which theimplantable cardiac function management device includes a detector foranother CHF symptom, such as a pulmonary fluid accumulation detector.

FIG. 7 is a block diagram of another example of an implantable cardiacfunction management device that includes an apnea detector and an apneaclassifier.

DETAILED DESCRIPTION

The following detailed description includes references to theaccompanying drawings, which form a part of the detailed description.The drawings show, by way of illustration, specific embodiments in whichthe invention may be practiced. These embodiments, which are alsoreferred to herein as “examples,” are described in enough detail toenable those skilled in the art to practice the invention. Theembodiments may be combined, other embodiments may be utilized, orstructural, logical and electrical changes may be made without departingfrom the scope of the present invention. The following detaileddescription is, therefore, not to be taken in a limiting sense, and thescope of the present invention is defined by the appended claims andtheir equivalents.

In this document, the terms “a” or “an” are used, as is common in patentdocuments, to include one or more than one. In this document, the term“or” is used to refer to a nonexclusive or, unless otherwise indicated.Furthermore, all publications, patents, and patent documents referred toin this document are incorporated by reference herein in their entirety,as though individually incorporated by reference. In the event ofinconsistent usages between this document and those documents soincorporated by reference, the usage in the incorporated reference(s)should be considered supplementary to that of this document; forirreconcilable inconsistencies, the usage in this document controls.

FIG. 1 is a block diagram illustrating generally an example of a system100 including an implantable device 102, which is typically wirelesslycommunicatively coupled by a communication module 103 to an externallocal interface 104, which, in turn is communicatively coupled to anexternal remote server 106, such as over a wired or wirelesstelecommunications or computer network 108. In certain examples, theimplantable device 102 includes an implantable cardiac functionmanagement device 102, such as a pacer, cardioverter, defibrillation,cardiac resynchronization therapy (CRT) device, or a combination devicethat combines these or other functions, such as patient monitoring,therapy control, or the like.

In this example, the implantable device 102 can include a hermeticallysealed housing to carry electronics, and can include a respirationmonitor 110, a sleep detector circuit 112, and an exercise detectorcircuit 114. In the example of FIG. 1, the respiration monitor 110includes a respiration detector circuit 116 that transduces a subject'sbreathing into an electrical signal representative of such breathing. Anexample of a respiration detector circuit 116 is a transthoracicimpedance sensor, which detects variations in transthoracic impedance asa subject inhales and exhales, such as described in Hartley et al. U.S.Pat. No. 6,076,015, which is incorporated herein by reference in itsentirety, including its description of an impedance-based respirationdetector. In other examples, a respiration signal can be derived fromdetected heart sounds, detected blood pressures, or one or more otherproxy parameters. An example of a sleep detector 112 is described inYousafali Dalal et al. U.S. patent application Ser. No. 11/458,602,entitled “SLEEP STATE DETECTION”, filed on Jul. 19, 2006, which isincorporated by reference in its entirety, including its description ofa sleep detector. An example of an exercise detector 114, is anaccelerometer, which can be configured to produce a signalrepresentative of the subject's activity, which, in turn, can besignal-processed to obtain an indication of a representative level ofactivity. For example, a rate-responsive pacer may already include anaccelerometer-based exercise detector to determine a patient activitylevel, so that the pacing rate can be adjusted according to the patientactivity level to adjust cardiac output according to a perceivedmetabolic need for such cardiac output.

In the example shown in FIG. 1, the respiration detector circuit 116 canreceive a sleep or awake indication from the sleep detector 112, and anexercise or resting indication from the exercise detector 114. Therespiration detector circuit 116 can output responsive signalsindicative of respiration during sleep, respiration during exercise, andrespiration while awake and at rest. In the example of FIG. 1, suchsignals are received by a disordered breathing detector 118. AlthoughFIG. 1 has been illustrated, for conceptual clarity, as having separatesignals representing respiration during sleep, respiration duringexercise, and respiration while awake and at rest, it is understood thatthe disordered breathing detector 118 can alternatively be implementedto receive a single respiration signal, together with sleep/awakeinformation from the sleep detector 112 and exercise/rest informationfrom the exercise detector 114.

However implemented, the disordered breathing detector 118 willtypically compute a separate indication of the amount of disorderedbreathing occurring during at least one of sleep, exercise, and restingawake states, which can be denoted as DB_(sleep), DB_(exercise), andDB_(rest), respectively. More typically, the disordered breathingdetector 118 will typically compute separate indications of the amountof disordered breathing occurring during at least two of sleep,exercise, and resting awake states, which can be denoted as DB_(sleep),DB_(exercise), and DB_(rest), respectively. Even more typically, thedisordered breathing detector 118 will compute three separateindications of the amount of disordered breathing occurring during eachof sleep, exercise, and resting awake states.

Such disordered breathing can include incidences of apnea. Apnea occurswhen breathing stops for a brief period, which may then be followed byhyperventilation. In certain examples, cessation of breathing for aperiod of at least 10 seconds is deemed an apnea event. Sleep disorderedbreathing can also include incidences of hypopnea. Hypopnea occurs whenbreathing amplitude decreases for a brief period, which may then also befollowed by hyperventilation. In certain examples, a drop in breathingamplitude by at least 30%-50% (and which does not constitute apnea) fora period of at least 10 seconds is deemed a hypopnea event. Anapnea-hypopnea index (AHI) can be defined as the number of apnea andhypopnea events during a period of sleep divided by the duration of thatperiod of sleep.

However, disordered breathing can also include hypopnea events that canoccur even if the patient is awake, such as when the patient is awakeand resting, or when the patient is awake and exercising. Whether whenawake or asleep, if such hypopnea events become frequent enough, theycan be deemed periodic breathing, which can be conceptualized as arecurring cycle of a hypopnea event, which followed by a period ofrespiration (which is often hyperventilation to offset the hypopnea).Hypopnea events or periodic breathing occurring during exercise, forexample, is believed to have different clinical significance than suchincidences occurring during sleep, and such incidences occurring whenthe subject is awake but at rest. Periodic breathing during exercise issometimes referred to as exertional oscillatory ventilation (EOV). Ingeneral, patients having AHI<30 and no EOV are believed to expect abetter survival rate than patients with EOV alone, who are believed, inturn, to expect a better survival rate than patients with AHI>30 alone(but no EOV), who are believed, in turn, to expect a better survivalrate than patients with combined breathing disorder (CBD), that is, bothAHI>30 and EOV. Thus, by categorizing disordered breathing, such asaccording to sleep, exercise, and resting awake states, a more accuratepatient wellness indicator can be created than by computing disorderedbreathing without distinguishing between whether such disorderedbreathing occurs during a sleep, an exercise, or a resting awake state.Such more specific wellness indicator(s) can be provided to an alertdetermination module 120 and used to provide a more accurate alert, suchas to the patient, to the patient's physician, or to the patient'spersonal medical device that initiates or adjusts one or more responsivetherapies. In the example of FIG. 1, the alert determination module 120can provide resulting alert to an alert response module 122, which cansound a buzzer, or communicate an alert via communication module 103 toexternal local interface 104 (e.g., a patient interface), or to anexternal remote server 106, which can provide remote monitoring andnotification of the patient or the patient's physician. Alternatively oradditionally, in the example of FIG. 1, the alert response module 122can provide closed-loop feedback to a therapy controller 124, which caninitiate or adjust one or more congestive heart failure (CHF) or othertherapies to be automatically delivered to the patient, such as cardiacresynchronization therapy (CRT), drug delivery, or any other suitableresponsive therapy. Examples of CRT include, without limitation,adjusting AV delay, adjusting interventricular pacing delay, adjustingintraventricular pacing delay, adjusting intraventricular electrodeselection, adjusting cardiac contractility modulation (CCM) therapy, orthe like.

The disordered breathing detector 118 can be configured to count anumber of apnea or hypopnea events, and to compute an overall unweighteddisordered breathing severity indication. In certain examples, thisdisordered breathing severity indication can be determined using a“density” (e.g., frequency or rate of occurrence) of such events perunit time. Similarly, the disordered breathing detector 118 can beconfigured to compute separate disordered breathing severity indicationsfor sleep, exercise, and awake and resting states. Such separatedisordered breathing severity indications for sleep, exercise, and awakeand resting states can be separately (e.g., differently) weighted andcombined into an overall weighted disordered breathing severityindication, which can in certain examples represent a density of suchevents per unit time. The disordered breathing severity indication canadditionally or alternatively use other information to determineseverity, such as a duration of a disordered breathing episode, ameasure of the amount of decrease of the respiration amplitude duringthe episode, or any other information that is indicative of the severityof the disordered breathing episode.

FIG. 2 is a flow chart illustrating generally an example of portions ofa technique for monitoring disordered breathing. In the example of FIG.2, at 200, respiration is monitored for incidences of disorderedbreathing, such as an apnea event or a hypopnea event, as discussedabove. At 202, if such a disordered breathing (DB) event is detected,then at 204, it is determined whether the subject was sleeping,otherwise process flow returns to 200. At 204, if the subject wassleeping when the DB event was detected, then a DBsleep density orseverity indicator is updated at 206. In certain examples, this caninvolve computing an inverse of a time period since the last DB eventwas detected in either a sleep, exercise, or resting state, andincluding this value in a buffer of the N most recent similar valuesoccurring during sleep. At 204, if the subject was not sleeping when theDB event was detected, then at 208 it is determined whether the subjectwas exercising when the DB event was detected. If so, then at 210, aDBexercise density or severity indicator is updated, similar to theupdating of the DBsleep density or severity indicator at 206. Otherwise,then at 212, a DBrest density or severity indicator is updated, similarto the updating of the DBexercise density or severity indicator at 210and the DBsleep density or severity indicator at 206. In this manner,separate indications of the severity or density over time of disorderedbreathing are computed for the sleep, exercise, and awake but restingstates.

FIG. 3 is a flow chart illustrating generally an example of how theDBsleep density or severity indicator, the DBexercise density orseverity indicator, and the DBrest density or severity indicator can beused. At 302, the DBsleep density or severity indicator is compared to athreshold value, which can be programmed specifically for the DBsleepdensity or severity indicator. At 304, the DBexercise density orseverity indicator is compared to a threshold value, which can beprogrammed specifically for the DBexercise density or severityindicator. At 306, the DBrest density or severity indicator is comparedto a threshold value, which can be programmed specifically for theDBrest density or severity indicator. At 308, if at least two of thesecomparisons exceed their respective threshold value, then an alert istriggered at 310, otherwise process flow returns to 200, whererespiration monitoring continues.

Variations on this technique are also possible. For example, at 308, thecondition could be defined such that if at least one of the comparisonsexceeds its respective threshold value, then an alert is triggered at310. Alternatively, at 308, the condition could be defined such that allthree comparisons must exceed their respective threshold values for thealert to be triggered at 310. In any of these various examples, thecorresponding threshold can optionally be set using a long-term averageor baseline of the particular one of the DBsleep density or severityindicator, the DBexercise density or severity indicator, and the DBrestdensity or severity indicator. In this manner, an alert will only betriggered if there is a more than insubstantial (e.g., 3 standarddeviations above baseline) change in one or more than one of suchdensity or severity indicators, depending on which test condition isused.

FIG. 4 is a flow chart illustrating generally an example of how theupdated DBsleep indicator, the DBexercise indicator, and the DBrestindicator can be used. After these respective indicators are updated,such as at 206, 210, and 212, respectively, then at 400, a combinedmetric DBtotal is updated, such as according toDBtotal=A·DBsleep+B·DBexercise+C·DBrest, where A, B, C are independentlyspecified scaling values. Then, at 402, the combined metric DBtotal iscompared to a corresponding threshold value. If, at 402, DBtotal exceedsits corresponding threshold value, then at 404 an alert is triggered,otherwise process flow returns to the respiration monitoring at 200.

In certain variations of the above technique, the combined metricDBtotal is logged, such as on a daily basis. Moreover, the threshold towhich the DBtotal metric is compared can be set based on a baselinelong-term value of the same metric, or based on the baseline value andvariance (e.g., threshold at +3 standard deviations above baseline).

FIG. 5 is a flow chart, similar to FIG. 2, but illustrating a techniquein which a periodic breathing (PB) event is detected at 502, instead ofdetecting a disordered breathing (DB) event at 202 of FIG. 2. A PB eventcan be conceptualized as a DB event (e.g., apnea or hypopnea) that isrecurring often enough and with sufficient periodicity to be consideredperiodic breathing instead of a series of isolated DB events. Oneexample of disordered breathing is described in Yachuan Pu et al. U.S.patent application Ser. No. 11/392,365 entitled “PERIODIC DISORDEREDBREATHING DETECTION”, filed on Mar. 28, 2006, which is incorporatedherein by reference in its entirety, including its description ofdetecting periodic breathing. In brief, periodic breathing can bedetected by rectifying the respiration signal, and lowpass filtering therectified signal (e.g., such as with a moving average) to obtain an“envelope” signal. The resulting envelope signal can be further filtered(e.g., highpass filtered to remove baseline wander) and then tested foramplitude variations of sufficient magnitude to constitute periodicbreathing. Periodic breathing density or severity indicators can becomputed for sleep, exercise, or resting states at 506, 510, and 512respectively, similarly to the above description of computing disorderedbreathing density or severity indicators for similar states at 206, 210,and 212, respectively of FIG. 2.

Disordered breathing and periodic breathing can be symptomatic ofcongestive heart failure (CHF). Therefore, in generating any alert basedon disordered breathing or periodic breathing, it may be desirable toqualify or otherwise base such alert on one or more other detectedsymptoms of CHF. For example, FIG. 6 illustrates a block diagram of anexample, similar to FIG. 1, in which the implantable cardiac functionmanagement device 602 includes an auxiliary CHF indication detector 604.As an illustrative example, the auxiliary CHF indication detector 604includes a pulmonary fluid accumulation detector to detect accumulationof pulmonary fluid, which is another symptom of CHF. The pulmonary fluidaccumulation detector can measure transthoracic impedance, which willtend to decrease as pulmonary fluid accumulates in the thorax. Thepulmonary fluid accumulation detector can itself include a posturedetector, to reduce or eliminate the effect of postural changes inthoracic impedance measurements to get a more accurate representation ofpulmonary fluid accumulation. Other examples of the auxiliary CHFindication detector 604 include a pulmonary artery pressure sensor, aheart sound sensor, a heart rate variability (HRV) sensor, a patientweight indicator (which may receive information communicated from anexternal weight scale), a patient activity sensor, or the like. Theauxiliary CHF indication detector 604 can also combine multiple suchsensors to provide various indications of CHF.

In the example in which the auxiliary CHF indication detector 604includes a pulmonary fluid accumulation detector, an indication ofdetected pulmonary fluid can be provided to the alert response module122. The indication of detected pulmonary fluid can be used to generatea separate alert, or to qualify an alert based on disordered or periodicbreathing, such that both pulmonary fluid accumulation and one or bothof disordered or periodic breathing is required in order to trigger theresponsive alert. Alternatively or additionally, the pulmonary fluidaccumulation indication (or any other appropriately weighted indicationsof one or more other CHF symptoms) can be appropriately weighted andcombined with the disordered breathing indication (or any otherappropriately weighted indications of one or more other CHF symptoms) tocreate a CHF status indicator representative of a CHF patient's wellnessor sickness based on multiple symptoms.

FIG. 7 is a block diagram of another example of an implantable cardiacfunction management device 702 that includes an apnea detector 704 andan apnea classifier 706. In this example, the apnea detector 704receives respiration during sleep information from the respirationdetector 116, and detects incidences of apnea. The apnea detector 704provides information about detected incidences of apnea to the apneaclassifier 706, which classifies the apnea, for example, as obstructivesleep apnea (OSA) or central sleep apnea (CSA). One illustrative exampleof a sleep apnea detector and classifier is described in Patangay et al.U.S. patent application Ser. No. 11/425,820, filed on Jun. 22, 2006,entitled APNEA TYPE DETERMINING APPARATUS AND METHOD, which isincorporated herein by reference in its entirety, including itsdescription of an apnea detector and classifier.

Since CSA is more likely to be indicative of CHF than OSA, the apneaclassification information provided by the apnea classifier 706 to thedisordered breathing detector 118 can be used to either: (1) qualify thedisordered breathing during sleep density or severity indicator, suchthat only CSA episodes are counted, and CSA episodes are not counted; or(2) provide separate disordered breathing during sleep density orseverity indicators to separately count incidences of OSA and CSA, withthe DB alert determination module 120 formulating its alert based onthese separate indicators similar to the manner described above.

Although the above description has emphasized an example in whichprocessing is generally carried out within an implantable device, itshould be understood that information derived from the respirationsignal obtained from the implantable device can be communicated toexternal local interface 104 or external remote server 106 to performsuch processing at such other locations. Moreover, such processing caninclude information from one or more devices that are not implanted. Forexample, a body weight measurement as measured by an external weightscale could be combined with a disordered breathing indication obtainedfrom an implantable cardiac function management device, e.g., duringprocessing at external remote server 106, to generate a CHF wellnessindicator or to trigger an alert or responsive therapy.

In certain examples, information from the disordered breathing detector118 (e.g., indications of disordered breathing density or severity insleep, exercise, or awake but resting states) can be provide to thecommunication module 103, and communicated to the external localinterface 104 or the external remote server 106, such as for storage orfor display on a monitor, for example, as separate trends of disorderedor periodic breathing density or severity in sleep, exercise, or awakebut resting states, or as histograms of disordered or periodic breathingdensity or severity in sleep, exercise, or awake but resting states, orin any other useful form.

It is to be understood that the above description is intended to beillustrative, and not restrictive. For example, the above-describedembodiments (and/or aspects thereof) may be used in combination witheach other. Many other embodiments will be apparent to those of skill inthe art upon reviewing the above description. The scope of the inventionshould, therefore, be determined with reference to the appended claims,along with the full scope of equivalents to which such claims areentitled. In the appended claims, the terms “including” and “in which”are used as the plain-English equivalents of the respective terms“comprising” and “wherein.” Also, in the following claims, the terms“including” and “comprising” are open-ended, that is, a system, device,article, or process that includes elements in addition to those listedafter such a term in a claim are still deemed to fall within the scopeof that claim. Moreover, in the following claims, the terms “first,”“second,” and “third,” etc. are used merely as labels, and are notintended to impose numerical requirements on their objects.

The Abstract is provided to comply with 37 C.F.R. §1.72(b), whichrequires that it allow the reader to quickly ascertain the nature of thetechnical disclosure. It is submitted with the understanding that itwill not be used to interpret or limit the scope or meaning of theclaims. Also, in the above Detailed Description, various features may begrouped together to streamline the disclosure. This should not beinterpreted as intending that an unclaimed disclosed feature isessential to any claim. Rather, inventive subject matter may lie in lessthan all features of a particular disclosed embodiment. Thus, thefollowing claims are hereby incorporated into the Detailed Description,with each claim standing on its own as a separate embodiment.

1. A system comprising: a sleep detector, adapted to detect a sleep indication in a subject, the sleep indication providing an indication or inference of whether the subject is asleep or awake; an exercise detector, adapted to detect an exercise indication in the subject, the exercise indication providing an indication or inference of whether the subject is active or at rest; and an implantable respiration monitor, operatively coupled to the sleep and exercise detectors, the respiration monitor adapted to detect disordered breathing in the subject, and to compute a sleep disordered breathing indication (DBsleep), an exercise disordered breathing indication (DBexercise), and a resting awake disordered breathing indication (DBrest), wherein the respiration monitor is configured to compute a combined disordered breathing metric, DBtotal, according to DBtotal=A·DBsleep+B·DBexercise+C·DBrest, wherein A, B, and C are independently specified scaling values.
 2. The system of claim 1, comprising an alert module, operatively coupled to the respiration monitor, the alert module generating an alert in response to an abnormal value of at least one of: the sleep disordered breathing indication, the exercise disordered breathing indication, and the resting awake disordered breathing indication.
 3. The system of claim 2, comprising an ambulatory therapy module, operatively coupled to the alert module, the ambulatory therapy module configured to automatically initiate or adjust therapy in response to the alert.
 4. The system of claim 1, comprising an alert module, operatively coupled to the respiration monitor, the alert module generating an alert in response to at least a specified increase in at least one of the sleep disordered breathing indication, the exercise disordered breathing indication, and the resting awake disordered breathing indication.
 5. The system of claim 4, comprising an ambulatory therapy module, operatively coupled to the alert module, the ambulatory therapy module configured to automatically initiate or adjust therapy in response to the alert.
 6. The system of claim 1, comprising an alert module, operatively coupled to the respiration monitor, the alert module generating an alert in response to at least an abnormal value or a specified increase in at least two of: the sleep disordered breathing indication, the exercise disordered breathing indication, and the resting awake disordered breathing indication.
 7. The system of claim 6, comprising an ambulatory therapy module, operatively coupled to the alert module, the ambulatory therapy module configured to automatically initiate or adjust therapy in response to the alert.
 8. The system of claim 1, comprising: an auxiliary congestive heart failure (CHF) indication detector; and an alert module, operatively coupled to the respiration monitor and the auxiliary CHF indication detector, the alert module generating an alert in response to an indication of CHF received from the CHF indication detector and an abnormal value or a specified increase of at least one of: the sleep disordered breathing indication, the exercise disordered breathing indication, and the resting awake disordered breathing indication.
 9. The system of claim 8, in which the auxiliary CHF indication detector includes a pulmonary fluid status indicator, and in which the indication of CHF received from the CHF indication detector includes an indication of an abnormally high level of pulmonary fluid.
 10. The system of claim 8, in which the auxiliary CHF indication detector includes at least one of a pulmonary artery pressure sensor, a heart sound sensor, a heart rate variability detector, a patient weight indicator, and a patient activity detector.
 11. The system of claim 8, comprising an ambulatory therapy module, operatively coupled to the alert module, the ambulatory therapy module configured to automatically initiate or adjust therapy in response to the alert.
 12. The system of claim 1, wherein the respiration monitor comprises: a respiration detector circuit, adapted to detect a respiration signal from the subject; an envelope detector circuit, adapted to detect an envelope of the respiration signal; and an envelope variation detector circuit, adapted to detect a variation in the envelope representing disordered breathing.
 13. The system of claim 1, wherein the respiration monitor comprises: means for detecting a respiration signal from the subject; and means for detecting separate indications of periodic breathing in each of sleep, exercise, and resting awake states.
 14. The system of claim 1, including an external display configured to display information about at least one of a sleep disordered breathing indication, an exercise disordered breathing indication, and a resting awake disordered breathing indication.
 15. The system of claim 14, in which the display is configured to display a trend over time of at least one of the sleep disordered breathing indication, the exercise disordered breathing indication, and the resting awake disordered breathing indication.
 16. The system of claim 1, including: an apnea classifier, configured to distinguish between obstructive sleep apnea (OSA) and central sleep apnea (CSA); and wherein the sleep disordered breathing indication uses information from the apnea classifier to determine the sleep disordered breathing indication.
 17. A system comprising: a sleep detector, adapted to detect a sleep indication in a subject, the sleep indication providing an indication or inference of whether the subject is asleep or awake; an exercise detector, adapted to detect an exercise indication in the subject, the exercise indication providing an indication or inference of whether the subject is active or at rest; an implantable respiration monitor, operatively coupled to the sleep and exercise detectors, the respiration monitor adapted to detect disordered breathing in the subject, and to compute at least two of: a sleep disordered breathing indication, an exercise disordered breathing indication, and a resting awake disordered breathing indication; and an alert module, operatively coupled to the respiration monitor, the alert module generating an alert in response to at least an abnormal value or a specified increase in at least two of: the sleep disordered breathing indication, the exercise disordered breathing indication, and the resting awake disordered breathing indication.
 18. The system of claim 17, comprising an ambulatory therapy module, operatively coupled to the alert module, the ambulatory therapy module configured to automatically initiate or adjust therapy in response to the alert.
 19. The system of claim 17, comprising an auxiliary congestive heart failure (CHF) indication detector, wherein the alert module is operatively coupled to the respiration monitor and the auxiliary CHF indication detector, the alert module generating an alert in response to an indication of CHF received from the CHF indication detector and an abnormal value or a specified increase of at least two of: the sleep disordered breathing indication, the exercise disordered breathing indication, and the resting awake disordered breathing indication.
 20. The system of claim 19, in which the auxiliary CHF indication detector includes a pulmonary fluid status indicator, and in which the indication of CHF received from the CHF indication detector includes an indication of an abnormally high level of pulmonary fluid.
 21. The system of claim 19, in which the auxiliary CHF indication detector includes at least one of a pulmonary artery pressure sensor, a heart sound sensor, a heart rate variability detector, a patient weight indicator, and a patient activity detector.
 22. The system of claim 19, comprising an ambulatory therapy module, operatively coupled to the alert module, the ambulatory therapy module configured to automatically initiate or adjust therapy in response to the alert.
 23. The system of claim 17, wherein the respiration monitor comprises: a respiration detector circuit, adapted to detect a respiration signal from the subject; an envelope detector circuit, adapted to detect an envelope of the respiration signal; and an envelope variation detector circuit, adapted to detect a variation in the envelope representing disordered breathing.
 24. The system of claim 17, wherein the respiration monitor comprises: means for detecting a respiration signal from the subject; and means for detecting separate indications of periodic breathing in each of sleep, exercise, and resting awake states.
 25. The system of claim 17, including an external display configured to display information about at least one of a sleep disordered breathing indication, an exercise disordered breathing indication, and a resting awake disordered breathing indication.
 26. The system of claim 25, in which the display is configured to display a trend over time of at least one of a sleep disordered breathing indication, an exercise disordered breathing indication, and a resting awake disordered breathing indication.
 27. The system of claim 17, including: an apnea classifier, configured to distinguish between obstructive sleep apnea (OSA) and central sleep apnea (CSA); and wherein the sleep disordered breathing indication uses information from the apnea classifier to determine the sleep disordered breathing indication. 